Learn the fundamentals
Build a clear foundation before moving into advanced workflows.
codit Course
Data Science and AI
Build a strong foundation in Python, analytics, machine learning and applied AI tools.
PythonNumPyPandasMatplotlibSQL
Course Overview
Learn by building real skills step by step.
Learn practical data workflows with Python, analysis libraries, visualization, SQL and machine learning fundamentals. You will also explore how AI tools support modern data work.
Build practical projects
Apply each stage of learning through focused project work.
Prepare for real development workflows
Practice the tools and processes used to complete real work.
Technology Stack
Tools and technologies covered
Core
- Python
- SQL
- Data analysis
- ML fundamentals
Frameworks
- NumPy
- Pandas
- Matplotlib
Tools
- AI tools
Learning Modules
What you will learn
01Python fundamentals for data workFocused learning with practical application.
Main topics
- Python fundamentals for data work
02Data cleaning and analysis with NumPy and PandasFocused learning with practical application.
Main topics
- Data cleaning
- analysis with NumPy
- Pandas
03Visualization with Matplotlib and reporting basicsFocused learning with practical application.
Main topics
- Visualization with Matplotlib
- reporting basics
04SQL for querying and analyzing structured dataFocused learning with practical application.
Main topics
- SQL for querying
- analyzing structured data
05Machine learning fundamentals and AI-assisted workflowsFocused learning with practical application.
Main topics
- Machine learning fundamentals
- AI-assisted workflows
Projects You'll Build
Portfolio-ready practice
Exploratory data analysis notebook
Apply the course concepts in a focused, practical build.
Technologies used
PythonNumPyPandas
Analyze datasets with Python
Data visualization report
Apply the course concepts in a focused, practical build.
Technologies used
NumPyPandasMatplotlib
Create practical data visualizations
Machine learning mini-project with practical insights
Apply the course concepts in a focused, practical build.
Technologies used
PandasMatplotlibSQL
Use SQL for data analysis
Skills and outcomes
Skills students will gain
- Analyze datasets with Python
- Create practical data visualizations
- Use SQL for data analysis
- Apply AI tools in data workflows
By the end
What students should be able to build
- Exploratory data analysis notebook
- Data visualization report
- Machine learning mini-project with practical insights
Ready to Start?
Ready to Start Data Science and AI?
Talk to our admissions team and choose the right learning mode.